Physical Sciences and Mathematics Commons^™

Ensemble Data Fitting For Bathymetric Models Informed By Nominal Data, Samantha Zambo

Dissertations

Due to the difficulty and expense of collecting bathymetric data, modeling is the primary tool to produce detailed maps of the ocean floor. Current modeling practices typically utilize only one interpolator; the industry standard is splines-in-tension.

In this dissertation we introduce a new nominal-informed ensemble interpolator designed to improve modeling accuracy in regions of sparse data. The method is guided by a priori domain knowledge provided by artificially intelligent classifiers. We recast such geomorphological classifications, such as ‘seamount’ or ‘ridge’, as nominal data which we utilize as foundational shapes in an expanded ordinary least squares regression-based algorithm. To our knowledge …

Microplankton Dynamics In The River-Dominated Mississippi Bight, Adam D. Boyette

Dissertations

The Mississippi Bight (MSB) is a river-dominated continental margin influenced by multiple large river systems, including the Mississippi River, Alabama and Tombigbee rivers via Mobile Bay, and numerous smaller rivers, creeks, and bayous. This is part of a biologically-rich ecosystem that supports the second largest fishery industry by volume in the United States. Despite our understanding of the linkages between primary production with higher trophic levels, there remains limited studies quantifying these trophic interactions in this system. Microplankton (µm) community dynamics and trophic connectivity between primary producers and heterotrophic protists represent a critical nexus influencing overall biological productivity in this …

Assessing The Real-Time Lagrangian Predictability Of The Operational Navy Coastal Ocean Model In The Gulf Of Mexico, Lea Kristen Locke

Dissertations

This study quantitatively assesses the drift predictive skill of Fleet Numerical Meteorology and Oceanography Center’s (FNMOC’s) operational ocean models which are used to support a wide range of military and civilian applications. Overall, the findings of this work support the recommendation of spatial filtering for regional-scale ocean model velocity fields used in deep-water drift applications. In conjunction with filtering, the use of a pure particle drift algorithm is suggested for short-term forecasts and a drift algorithm including a sub-grid scale, random flight, parameterization for predictions requiring extended forecast predictions.

Drift prediction skill is quantified through metrics of in-cloud percentage, distance …